Simulation of Molecular Interactions in the Life cycle of M13
Text by Nick Fisk
One of the grand challenges in biology is the development of a molecular level understanding of how genetically-encoded instructions are converted into the phenotypic behaviors of living systems. Naturally evolved systems often contain complex nested control mechanisms involving coordinated and competing protein-protein and protein-nucleic acid interactions. We are broadly interested in a developing a deep quantitative understanding of bacteriophages to enable their use in synthetic biology as general platforms for construction of materials and assemblies with biomedical applications. Our paper describes the integration of 50 years of experimental observations on M13 biology into computational simulation of the life cycle of this filamentous bacteriophage. We have used our model to evaluate the nested feedback control loops in the phage life cycle and to identify gaps in the quantitative understanding of M13 biology. One way to think about the simulation is as a microscope, we are using available biochemistry to produce a picture of what is happening in the course of the phage infection at the level of molecules updated on the time scale of seconds.
The major problem in any modeling effort is finding usable quantitative data to parameterize the model. Even in very well studied systems, there are parameters that are just not available and tuning the model to find the parameters that fit the experimental data is a challenge. This is especially the case when the quantitative experimental data you are trying to recapitulate is “soft”, that is approximate averages under not ideally specified conditions. Choosing the right balance of detail to data is also challenging. Early in the model building process, as new components were being added to the simulation, fixing one problem tended to create another. Ultimately the set of “unknown” parameters that allow our simulation to recapitulate the behavior of the phage are predictions about the values of experimentally determinable rate constants or cellular concentrations. We view our simulation as a powerful tool to collectively evaluate the accumulated biological information about M13 and as a framework for asking specific questions about how phage control processes are interrelated.
A particularly surprising finding from our simulation was an important role of a regulatory process involving the phage single stranded DNA binding protein. This protein, p5, is involved in phage DNA replication but also functions to regulate translation of phage proteins by binding mRNA. We found that a modest self-attenuation function of p5 is a critical control element that is necessary to allocate resources to phage particle production.
A) Depiction of the M13 bacteriophage life cycle from cell entry to release of progeny page. Question marks (?) indicate aspects of the life cycle for which the details of the molecular interactions are unknown. B) Control circuit diagram depicting dynamic, coordinated and competing protein-protein and protein-nucleic acid interactions that regulate the M13 lifecycle.
Introducing the authors
Left: first author Steven Smeal, Masters of Science in Engineering, 2014 and Graduate Research Assistant in the Fisk Lab, Colorado State University; Right: corresponding author John D. (Nick) Fisk, Boettcher Investigator and Assistant Professor at the Department of Chemical and Biological Engineering, Colorado State University
About the research
Simulation of the M13 life cycle I: Assembly of a genetically-structured deterministic chemical kinetic simulation
Steven W. Smeal, Margaret A. Schmitt, Ronnie Rodrigues Pereira, Ashok Prasad, John D. Fisk
Virology, Volume 500, January 2017, Pages 259–274